Body Weight Estimation in Holstein × Zebu Crossbred Heifers: Comparative Analysis of XGBoost and LightGBM Algorithms
ABSTRACT This study evaluates the effectiveness of XGBoost and LightGBM algorithms for estimating the live weight of Holstein×Zebu crossbred heifers. The study compares the performance of both algorithms using a wide range of biometric measurements and tests various hyperparameter settings. The rese...
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| Format: | Article |
| Language: | English |
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Wiley
2025-07-01
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| Series: | Veterinary Medicine and Science |
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| Online Access: | https://doi.org/10.1002/vms3.70422 |
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| author | Jose Herrera‐Camacho Cem Tırınk Rosa Inés Parra‐Cortés Lütfi Bayyurt Rashit Uskenov Karlygash Omarova Aizhan Makhanbetova Kadyrbai Chekirov Alfonso Juventino Chay‐Canul |
| author_facet | Jose Herrera‐Camacho Cem Tırınk Rosa Inés Parra‐Cortés Lütfi Bayyurt Rashit Uskenov Karlygash Omarova Aizhan Makhanbetova Kadyrbai Chekirov Alfonso Juventino Chay‐Canul |
| author_sort | Jose Herrera‐Camacho |
| collection | DOAJ |
| description | ABSTRACT This study evaluates the effectiveness of XGBoost and LightGBM algorithms for estimating the live weight of Holstein×Zebu crossbred heifers. The study compares the performance of both algorithms using a wide range of biometric measurements and tests various hyperparameter settings. The research results show that the XGBoost algorithm provides almost perfect agreement with an R2 value of 0.999 on the training set and high performance with an R2 value of 0.986 on the test set. The LightGBM algorithm also achieved effective results with R2 values of 0.986 and 0.981 on both training and test sets. The machine learning algorithms used in the current study stand out as having the potential to provide a practical and economical solution for live weight estimation in livestock enterprises and especially for herd management applications in rural areas through input variables such as body measurements, milk yield, etc. However, the obtained results in the current study reveal the potential of machine learning algorithms for live weight estimation in the livestock sector and indicate that advanced research is needed for the optimisation of these algorithms. |
| format | Article |
| id | doaj-art-e69f402f6e1f4ffda07f6c31ac8e98ef |
| institution | Kabale University |
| issn | 2053-1095 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Wiley |
| record_format | Article |
| series | Veterinary Medicine and Science |
| spelling | doaj-art-e69f402f6e1f4ffda07f6c31ac8e98ef2025-08-20T03:55:53ZengWileyVeterinary Medicine and Science2053-10952025-07-01114n/an/a10.1002/vms3.70422Body Weight Estimation in Holstein × Zebu Crossbred Heifers: Comparative Analysis of XGBoost and LightGBM AlgorithmsJose Herrera‐Camacho0Cem Tırınk1Rosa Inés Parra‐Cortés2Lütfi Bayyurt3Rashit Uskenov4Karlygash Omarova5Aizhan Makhanbetova6Kadyrbai Chekirov7Alfonso Juventino Chay‐Canul8Universidad Michoacana de San Nicolás de Hidalgo Morelia Michoacán MexicoDepartment of Animal Science Igdir University, Faculty of Agriculture Iğdır TürkiyeUniversidad de Ciencias Aplicadas y Ambientales U.D.C.A, Área de Ciencias Agropecuarias, Grupo de Investigación en Ciencia Animal Bogotá ColombiaFaculty of Agriculture Department of Animal Science Tokat Gaziosmanpaşa University Tokat TürkiyeAgronomic Faculty Saken Seifullin Kazakh Agrotechnical University Astana KazakhstanFaculty of Veterinary and Livestock Technology Saken Seifullin Kazakh Agrotechnical University Astana KazakhstanFaculty of Veterinary and Livestock Technology Saken Seifullin Kazakh Agrotechnical University Astana KazakhstanKyrgyz‐Turkish Manas University Bishkek Kyrgyz RepublicDivisión Académica de Ciencias Agropecuarias Universidad Juárez Autónoma de Tabasco Villahermosa Tabasco MéxicoABSTRACT This study evaluates the effectiveness of XGBoost and LightGBM algorithms for estimating the live weight of Holstein×Zebu crossbred heifers. The study compares the performance of both algorithms using a wide range of biometric measurements and tests various hyperparameter settings. The research results show that the XGBoost algorithm provides almost perfect agreement with an R2 value of 0.999 on the training set and high performance with an R2 value of 0.986 on the test set. The LightGBM algorithm also achieved effective results with R2 values of 0.986 and 0.981 on both training and test sets. The machine learning algorithms used in the current study stand out as having the potential to provide a practical and economical solution for live weight estimation in livestock enterprises and especially for herd management applications in rural areas through input variables such as body measurements, milk yield, etc. However, the obtained results in the current study reveal the potential of machine learning algorithms for live weight estimation in the livestock sector and indicate that advanced research is needed for the optimisation of these algorithms.https://doi.org/10.1002/vms3.70422body weight predictioncrossbred heiferLightGBMmachine learningXGBoost |
| spellingShingle | Jose Herrera‐Camacho Cem Tırınk Rosa Inés Parra‐Cortés Lütfi Bayyurt Rashit Uskenov Karlygash Omarova Aizhan Makhanbetova Kadyrbai Chekirov Alfonso Juventino Chay‐Canul Body Weight Estimation in Holstein × Zebu Crossbred Heifers: Comparative Analysis of XGBoost and LightGBM Algorithms Veterinary Medicine and Science body weight prediction crossbred heifer LightGBM machine learning XGBoost |
| title | Body Weight Estimation in Holstein × Zebu Crossbred Heifers: Comparative Analysis of XGBoost and LightGBM Algorithms |
| title_full | Body Weight Estimation in Holstein × Zebu Crossbred Heifers: Comparative Analysis of XGBoost and LightGBM Algorithms |
| title_fullStr | Body Weight Estimation in Holstein × Zebu Crossbred Heifers: Comparative Analysis of XGBoost and LightGBM Algorithms |
| title_full_unstemmed | Body Weight Estimation in Holstein × Zebu Crossbred Heifers: Comparative Analysis of XGBoost and LightGBM Algorithms |
| title_short | Body Weight Estimation in Holstein × Zebu Crossbred Heifers: Comparative Analysis of XGBoost and LightGBM Algorithms |
| title_sort | body weight estimation in holstein zebu crossbred heifers comparative analysis of xgboost and lightgbm algorithms |
| topic | body weight prediction crossbred heifer LightGBM machine learning XGBoost |
| url | https://doi.org/10.1002/vms3.70422 |
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